Comments (2)
stefanhgm
commented on September 6, 2024
Hello @pretty-speeches ,
thanks for using our code and please excuse the late reply.
It looks as if the dataset reader does not know about the car dataset. Did you use the t-few dataset and replace all files given in the TabLLM/t-few directory (see point 2 in the Readme). Especially, the TabLLM/t-few/src/data files seem to be relevant for your issue since they add our datasets to the ones of the t-few project.
Please let us know if that helps!
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stefanhgm
commented on September 6, 2024
Hello @pretty-speeches,
just as a heads-up: based on the feedback in the issues, we updated the readme now with all steps to reproduce a performance entry from the paper. Maybe that is also helpful for you!
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Related Issues (20)
- How can we use Llama2 here? HOT 3
- Could you please upload the entire source codes? HOT 2
- Element 0 of tensor does not require grad and does not have a grad_fn HOT 3
- Totally Can NOT Re-Produce!!! HOT 4
- Cannot reproduce performance on blood dataset with text template serialisations HOT 4
- Only dev_scores.txt available in exp_out folder HOT 1
- The scores after every 30 epochs doesn't change at all during fine-tuning HOT 1
- When I reviewed the code, I couldn't find the output of the model
- dev_scores.json is not found when num_shot is 0 HOT 6
- global.json not found HOT 3
- Error with Creating Serialized Datasets HOT 9
- Zero-shot inference with t-few does not produce the scores and inferences HOT 1
- AttributeError: Can't pickle local object 'get_linear_schedule_with_warmup.<locals>.lr_lambda' HOT 5
- How can I apply it to my own data set? HOT 1
- Key error: "probabilities" HOT 4
- GPT-3 zero-shot prediction HOT 3
- Custom dataset use HOT 1
- Requesting the 'pl_train' module from src HOT 4
- yaml template custom tag HOT 1
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